Title | Empirical analysis of daily cash flow time-series and its implications for forecasting |

Publication Type | Journal Article |

Year of Publication | 2018 |

Authors | Salas-Molina F [1], Rodríguez-Aguilar JA [2], Serrà J [3], Guillén M [4], Martin F [5] |

Journal | SORT-Statistics and Operation Research Transactions |

Volume | 42 |

Issue | 1 |

Pagination | 73-98 |

Date Published | 01/2018 |

Publisher | Statistical Institute of Catalonia |

Keywords | cash flow [6], forecasting [7], non-linearity [8], statistics [9], time-series [10] |

Abstract | Usual assumptions on the statistical properties of daily net cash flows include normality, absence of correlation and stationarity. We provide a comprehensive study based on a real-world cash flow data set showing that: (i) the usual assumption of normality, absence of correlation and stationarity hardly appear; (ii) non-linearity is often relevant for forecasting; and (iii) typical data transformations have little impact on linearity and normality. This evidence may lead to consider a more data-driven approach such as time-series forecasting in an attempt to provide cash managers with expert systems in cash management. |